{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Programming Exercise 6: Support Vector Machines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy.io #Used to load the OCTAVE *.mat files\n",
    "import scipy.optimize #fmin_cg to train the linear regression\n",
    "from sklearn import svm #SVM software"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1 Support Vector Machines"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.1 Visualizing the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "datafile = 'data/ex6data1.mat'\n",
    "mat = scipy.io.loadmat( datafile )\n",
    "#Training set\n",
    "X, y = mat['X'], mat['y']\n",
    "#NOT inserting a column of 1's in case SVM software does it for me automatically...\n",
    "#X =     np.insert(X    ,0,1,axis=1)\n",
    "\n",
    "#Divide the sample into two: ones with positive classification, one with null classification\n",
    "pos = np.array([X[i] for i in xrange(X.shape[0]) if y[i] == 1])\n",
    "neg = np.array([X[i] for i in xrange(X.shape[0]) if y[i] == 0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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mJLFYLvfWiBROlLoSGxsbaWxsLHUxREqq0FNp4O5PANu5+9b0dBofy/UC7r4l\n/XTH9PVe7uewERVepFja29upqekiOweLxaC6uov29vbSFUwkTV1HIpUjl+Rsi5m9C+gws/8ws0U5\nvg8AM4uZWTvwAtDq7o/0c9ihZtZhZneY2T65njsEof7CVdxhUdyVZagWvEqNeyiKW3I15Jgz4Ay6\nx5mdAyyie56zE3O9gLungLiZTQDuNLP5fW4oSAIz012fRwK3ATX9nSuRSFBVVQXApEmTqK2tzfwS\n6Kn8StvuEZXyFGu7o6MjUuV59dVXWbVqGnPmPEksBh0d3d2aa9bUEI/HVd8VVt/l8v+75/natWu5\n9tprM/tK/fuxZ5/qu/d2j6iUR/+/R3e75/natWvJV05ra44WM7sQ2OLuPxjkmKeBOnd/qc9+jTmT\nkuq5IaC6uvuGgDVrqmlouEY3BEgkaJyXSLQUZJ4zM/uVu59iZp10Tz7bi7vvm0PBdgHecvdXzWwM\n8BFgSZ9jprr7hvTzg+hOGF/a9mwipTV7dpzm5mRmjFk8HteNACIiMuoG+2b5cvrfo4Fj+nnkYhpw\nT3rM2Z+AFe5+l5l9zsw+mz7mJDN7OH3MpXQvrC5pfZvDQxHVuGOxGHV1ddTV1RUkMYtq3IWmuPOX\n3aUYdarvsIQadz4GbDlz9+fT0180u/vhIzm5u3cC+/ez/4qs5z8FfjqS84uISLdySs7KWfZYupDp\ncyisXOY5uws4wd1fLU6RBiyHxpyJiEhJaWxfN30OQyvU2po9NgOdZvZfwGs9O939SyO5oIiIiIgM\nLJfk7Nb0Q0oghKbjVCq1zSD7EOLuj+IOi+IuD62trZlxU/ksTVVucfc10s+h3OMuhSGTM3e/dqhj\nREZqoPUqRUSiom/yEWp3nj6H4sllzFk18B1gH+DdPfvdfc/CFm2bcmjMWYXRepUiUm401qqbPoeh\nFXptzWuAnwNvA4cDy4HrRnIxkWxar3JkUqkUyWSSZDJJKpUqdXFEgqLuuW76HAorl+RsjLvfRXcr\n2zp3bwSOKmyxpEeo88OsXr261EUoiaHqu7OznUSijpaWebS0zCORqKOzs/wT2VB/zhV3+cknKSnn\nuPsa7lg7GZ5ckrM3zCwGrDGzc8zseGB8gcslAYjH43R11ZDd+NOzXmV1dXXpChZRqVSKpqazSSQ6\nmDt3C3PnbiGR6KCp6Wy1oImIVJBcxpwdCDwKTAK+BUwAmtz9T4UvXq9yaMxZBdJ6lblLJpO0tMxj\n7twtvfbLORIUAAAfzElEQVS3tY1lwYJV1NXVlahkIiLSV6HW1jwZ+K27P5jetRk4ayQXERmI1qsU\nERHpbbBvwdOBZ8zsl2a2IL2UkxRZCH31/a1XGULc/Rks7sG6gePx8m5pVH2Hpb+4Q/gsQoixP6HG\nnY8BkzN3Px7YC/hv4N+AZ83scjObX6zCicg7YrEYDQ3LaG6upa1tLG1tY2lu3o+GhmVqbZSypy9w\nkXcMOeYsc6DZzsBJwBeAKe4+o5AF6+f6GnMmQv8rKoiUO82bJZWm0GtrYmaTgROAU4EpwH+O5GIi\nkr+ebmCRcjdayyKJVJoBW87MbDxwPLAQiAMrgJuA1lI0YYXachbqmmSKOyyKOyz9xR1Cy5nqOyyF\najlbC/we+BnwB3d/ayQXEBEREZHcDdZyNsbdXy9yeQYUasuZiEgIQm1dkcqVT8tZzjcElJqSMxER\nESkXhV74XEoo1NvLFXdYFHdYFHdYQo07H0rORERERCJksDFn2wGfBqYDv3f3+7Jeu8Ddv12cImau\nqW5NkQqkedtEpBIVqlvzCmA+8HfgMjP7YdZrJ4zkYiJRlkqlSCaTJJNJUtlrJEnBdHa2k0jU0dIy\nj5aWeSQSdXR2tpe6WCIiJTVYcnaQu5/u7pcCBwPjzexWM9sRGFEmKMMXal99seOOSpIQUn2nUima\nms4mkehg/PgtzJ27hUSig6ams4NJjkOq72yKOyw9cYca/0gMlpy9q+eJu7/t7p8FOoC7gfGFLphI\nsWQnCXPnhpkklEJ7ezs1NV1k92LGYlBd3ZXp5hSRyqHkLHeDJWerzexj2Tvc/WLgGqCqkIWSd4Q6\n708x445SkhBqfdfWlroEpRFqfSvusIQadz4GXCHA3T85wP6rgKsKViIRCUI8Hmfp0hrmzOnIJMap\nFKxZU0M8Hi9t4URkVGj91JHJaeFzKZ1QZ80uZtxRShJCqu9YLEZDwzKams5m++0fZY89tmPNmmoa\nGpYFc8dmSPWdTXGHoyfenn8rff3U0aLkTIKXnSRUV3cBBJcklMrs2XGam5NceeWVHHDAAZpKQ0QE\nLd8kkqH5tkRECie0lsOCr61pZrsDs8hqaXP3VSO54EgpORMRkdCEltBUkoKurWlm3wPuAy4AGtKP\nr43kYjJ8od56rLjDorjDorgL+56oqYQYii2XMWfHAf/s7m8UujAiIiIioRuyW9PMWoCT3X1zcYo0\nYDnUrSkiIhWv7/QTixcvBjT9RLnJp1szl5azLUCHmd0FZFrP3P1LI7mgiAyfblYQCUffJEzTT4Qn\nl9/wK4BvAf8XSGY9pAhC7atX3O+IyrqfhaT6DovGXoUl1LjzMWTLmbtfW4yCiMi2stf97GksmzOn\ne93P5uakWtAkGKHetRhizJLbmLOj6W4565lKwwB39wmFL16vcmjMmQQnmUzS0jKPuXO39Nrf1jaW\nBQtWUVdXV6KSiRRXY2OjuvekrBR6zNmlwAlAp7IjGS6NlRKRkdK6jBKqXL4pnwUeVmJWGuXcV5/P\nWKlyjjsffeOOx+N0ddWQSr2zrxIXB1d9hyXXuOvr6zMtZosXL848L9fETPUtucql5ezrQIuZtdL7\nbs0fDvVGM9sRWAW8K/243d3P7+e4y4AjgdeAhLt35FR6KYlcWsM0Vmp0aN1PEZHw5DLm7E5gM9AJ\nZP5+d/clA76p9/vHuvsWM9uO7pUGvuru92W9fiRwjrsfZWYHA0vd/ZB+zqPGuwjo7Gynqelsamq6\nE4WurhoaGpYxe3bvVhyNlRpd6h6W0IV6Q4CUr0KPOXuPu39gJCcHcPeeb+cd6e5GfbnPIccCy9PH\n3m9mE81sqrtvGOk1pTDUGlY6sVhMCa0ETYmZhCSXb9OVZvbRkV7AzGJm1g68ALS6+yN9DtkdWJ+1\n/df0PiFaffXt7e3U1HSRnYPFYlBd3ZVp1emR71ipKMVdTIo7LIo7LIpbcpVLy9nnga+Z2RvAWwxz\nKg13TwFxM5sA3Glm89393pEUNpFIUFVVBcCkSZOora3N/DXVU/mVtt0jCuV5/PHHM+XpSI8KrK3t\n/nf16tVs2rQpc/yqVauor/8Czc0/o7q6i6ef3sqzz07nBz/oHis11PU60hco9ecfcn0XczuK9Z1K\npZg4cSIAr776KrFYTPVdwfVdjO0eUSmP6nt0t3uer127lnwNOeZsNJnZhcAWd/9B1r7LgXvc/eb0\n9mPA/L7dmhpzVnqpVIpEoq5Xt2YqBc3NtQN2a2qslJSjXMdWiogMJJ8xZ7ncEDCvv/3uviqHgu0C\nvOXur5rZGOAPwBJ3vyvrmAXAF9M3BBwCXKobAqKr50ur952D1+hLSyrGSP4IERHpK5/kLJffMg1Z\njwuB3wKNOZ5/GnBPeszZn4AV7n6XmX3OzD4L4O4rgafN7AngCuALwwuhsvVtDi+12bPjNDcnWbBg\nFQsWrKK5+aGCJGajGXcqlSKZTJJMJkllD4KLoKjVd7FEKe7hjK3MV5TiLibFHZZQ485HLmtrHpO9\nbWYz6F41YEju3gns38/+K/psn5PL+SQayunOwb7dU0uXqnuqUNSFLSIyOoY95szMDPgfd9+nMEUa\n8Lrq1pRhUfdU8VTSGC393IjIaCj0mLMfAz0HxYBaYK27f3IkFxwpJWcyXJoItzgqMZnR2EoRyVeh\nx5ytBpLpx/8PfL3YiVnIQu2rV9zlYzTGaEUt7lKMrSynsZH5ilp9F4villzlMubs2mIURGS0xeNx\nli6tYc6c3i06lbZouBRGMcdWamykiGQbsFvTzDp5pzuz10t0T0K7byEL1k951K0pw6buqcKrxG7N\nYtLnJ1KZCjLmzMxmDfZGd183kguOlJIzGSndRVh4SoJHTmMjRSpTQcacufu6ngfwD2B2+vF6sROz\nkIXaVz+acfd0T9XV1UU+MSvX+s53jFa5xp0vxR2WXOOutM+n0uIphiG/qczsFOAB4GTgFOB+Mzup\n0AUTkfJSTklwlMTjcbq6asi+B0BjI8OmZEZymUrjz8BH3P1/09u7Av/t7vsVoXzZ5VC3pohUJHUL\nS7bGxkYaGxtLXQzJUz7dmkPerQnEehKztL+T2xQcIiKSg55uYY2NDFdra2umxWzJkiWZ/fX19dTX\n15emUFIyubScNQH7Ajemd50KdLr7/1fgsvUtR5AtZ62trUH+x1TcYVHcYVHcg6u0lrNQ67ugLWfu\n3mBmJwBz07t+4e6/GcnFRERERGRwg02lsRcw1d3v67N/LvC8uz9ZhPJlXzfIljORSqDpTERyF2pL\nU6Up1PJNlwIb+9n/avo1EZEhdXa2k0jU0dIyj5aWeSQSdXR25rask0iIlJjJYMnZVHfv7Lszva+q\nYCWSXkK9pVpxV4ZUKkVT09kkEh3MnbuFuXO3kEh00NR0dq/1Iyst7lwp7rAobsnVYMnZpEFeGzPa\nBRGRyjMai6KLiIRmsDFnNwJ3u/uVffZ/mu55z04tQvmyr6sxZyJlRksTiUioCnW35rnAb8zsE0Ay\nve8A4F3A8SO5mIiEJR6Ps3RpDXPm9F7UW7Pfi4gMbLC1NTe4+xxgCbA2/Vji7oe6+wvFKZ6E2lev\nuCtDLBajoWEZzc21tLWNpa1tLM3N+9HQsKzXHZuVFneuFHdYFLfkKpd5zu4B7ilCWUSkApXD7Pea\n6kNEomTIFQKiQmPORKQQeta1rKnpXteyq6uGhoZlWtdSRPKSz5gzJWciEaYWncJKpVIkEnUkEr3H\nxDU319LcnNTnLSIjVqhJaCUCKrmvPpVKkUwmSSaTvea8gsqOezDZcYc0eWup6rvUU33o5zwsilty\npeRMSiKkxGMkcp28VUREKo+6NaXo1JU0NM0PVhz6WRSRQinUPGciBTFUV5ISDymWnqk+mprOprq6\n+4aANWuqt5nqQ0SkmPTbJ+JC7asPPe54PE5XVw3ZPZiVPHlrKeu7Z6qPBQtWsWDBKpqbHxq1OzUH\nG1cJ+jkPjeKWXCk5k6ILLfEYiVwnb5XREYvFqKuro66ubtQ+33IfVzlUYikihaMxZ1ISPXNL9e5K\nukZzS/WhqTTKU7mPZdPcbyL50zxnUpaUeEilKucbOso9sRSJCs1zVsEqua9+sK6kSo57MIo7LFGM\nuxhzv0Ux7mJQ3JIrJWcyII05ERkZjasUkXyoW1P6pTEnIvkp13GV6tYUGR0acyajSr+cRUZHuY6r\nLNfEUiRKNOasgpWir77U6w1CuGMUFHdlGWqKjqjGXci53yC6cRea4pZcaYUAERHZRk9iKSLFp25N\n2Ya6NUVERPKjMWcy6jTmREREZOQiO+bMzKab2d1m9j9m1mlmX+rnmPlm9oqZPZR+XFDIMpWbUvXV\nF3rMyVBCHaOguMOiuMOiuCVXhR5z9jbwFXfvMLPxQNLM7nT3x/oct8rdP17gssgwacyJiIhI8RW1\nW9PMbgN+7O53Ze2bD3zN3Y8Z4r3q1hQREZGyENluzWxmVgXUAvf38/KhZtZhZneY2T7FKpOIiIhI\n1BQlOUt3af4n8GV339zn5SQw091rgZ8AtxWjTOUi1L56xR0WxR0WxR2WUOPOR8HnOTOz7elOzH7p\n7rf3fT07WXP3FjP7mZlNcfeX+h6bSCSoqqoCYNKkSdTW1lJfXw+8U/mVtt0jKuUp1nZHR0ekyqP6\nLuy26jsa5VF9F3a7R1TKo/oe3e2e52vXriVfBR9zZmbLgRfd/SsDvD7V3Teknx8E/Mrdq/o5TmPO\nREREpCzkM+asoC1nZnYY8Amg08zaAQfOB2YB7u6/AE4ys88DbwGvA6cWskwiIiIiURYr5Mnd/T53\n387da9097u77u/vv3f2KdGKGu//U3T+Qfn2Ou/d3w0Cw+jaHh0Jxh0Vxh0VxhyXUuPNR0ORMRERE\nRIZHyzeJVLhUKkV7ezsA8Xhca6OKiBRBWcxzJiLF19nZTiJRR0vLPFpa5pFI1NHZ2V7qYomIyCCU\nnEVcqH31ijt/qVSKpqazSSQ6mDt3C3PnbiGR6KCp6WxSqdSoXWc0hFjfqVSKK664gmQyGbn6KLQQ\n6xsUt+ROyZlIhWpvb6empovsXsxYDKqruzLdnFIaPS2aDzzwZbVoisg2NOZMpEIlk0laWuYxd+6W\nXvvb2sayYMEqLWpfIqlUikSijkSiI5M4p1LQ3FxLc3NSYwJFKoTGnInINuLxOF1dNWT3mKVSsGZN\nDfF4vHQF6yOVSpFMJoPp3lOLpogMRclZxIXaV6+48xeLxWhoWEZzcy1tbWNpaxtLc/N+NDQsi0zr\nTE/33s9+dliQ3XvpVW2Co//fYQk17nwUfG1NESmd2bPjNDcnIzmVRvYNC3/5C9TWwpw53TcsVHL3\nXjweZ+nSGubMeSczi2KLpoiUjsacSdA0B1jphDwmrrOznaams6mu7gJgzZpqGhquYfZsJWcilSKy\na2uKRFnPF2RNTfcX5NKlNTQ0LNMXpBRclFs0RaT09Nsg4kLtqy903FGdAyyk+s6+YaFn7FVI3Xux\nWIxNmzZRV1cXXGIW0s95NsUtuVLLmQRpqDvmKrlLLSp6blhoajqb7bd/lE2btkt370XnhgUpDg0v\nEOlNY84kSCGPd4oafTGHre/wgq4uDS+QypDPmDMlZxIkTQQqUnr6fyiVTJPQVrBQ++oLHXdU5wBT\nfYcl9LhDm5A39PqW3GnMmQRLd8yJiEgUqVtTRERKQt2aUsk05kxERMqSJuSVSqUxZxUs1L56xR0W\nxR2W7Lh7hhcsWLCKBQtW0dz8UMUmZqpvyZXGnImISEnFYjFNXyOSRd2aIhIUzasmIsWgbk0RkRx0\ndraTSNTR0jKPlpZ5JBJ1dHZW3pQNIlLelJxFXKh99Yo7LMWIO4rrqaq+w6K4JVdKzkQkCKFNeCoi\n5UtjzkQkCFpPVUSKSWPORESGEI/H6eqqIbsHM5WCNWtqiMcrc+oGESlPSs4iLtS+esUdlmLEHcX1\nVFXfYVHckivNcyYiwdB6qiJSDjTmTERERGSUacyZiIiISIVQchZxofbVK+6wKO6wKO6whBp3PpSc\niYiIiESIxpyJiIiIjLJ8xpzpbk0RGTEtIi4iMvr0mzTiQu2rV9zRN5qLiJdT3KNJcYdFcUuu1HIm\nIsOWvYh4T2PZnDndi4g3NyfVgjaAvi2NIiL90ZgzkRIrx65BrVM5fJ2d7TQ1nU1NTRcAXV01NDQs\nY/ZsJWkilUjznImUqdHsGpToym5pnDt3C3PnbiGR6G5pTGUv9ikiQoGTMzObbmZ3m9n/mFmnmX1p\ngOMuM7M1ZtZhZrWFLFO5CbWvPoS4+/vCrq0tjy/s0V5EvNLru729nZqaLrIbRWMx2H77RzOtpiGp\n9PoeiOKWXBV6zNnbwFfcvcPMxgNJM7vT3R/rOcDMjgTe6+7VZnYwcDlwSIHLJVJyA31hV1d30d7e\nHumuwZ5FxJuazqa6urubbs2a6pIuIi4iUimKOubMzG4Dfuzud2Xtuxy4x91vTm8/CtS7+4Y+79WY\nM6kolTBuqxzHy5VCKpUikajrdQNFKgXNzbW6gUKkQpXFPGdmVgXUAvf3eWl3YH3W9l/T+zYgUsHi\n8ThLl9YwZ07vL+yRdg2WQiwWK4skstTU0igiw1GU3wrpLs3/BL7s7puLcc1KEWpffQhx93xhNzfX\n0tY2lra2sXz3u+8N8gs7hPqePTtOc3OSBQtWsWDBKpqbH+Lvf3+11MXKSKVSJJNJkslkwcc8hlDf\n/VHckquCt5yZ2fZ0J2a/dPfb+znkr8CMrO3p6X3bSCQSVFVVATBp0iRqa2upr68H3qn8StvuEZXy\nFGu7o6MjUuUp5HZzc5Irr7wSgG98o5rZs+ORKl8xtkOq77q6OlpbW1m1ahU9Sl2+Zcuu5Kabvse8\nec8DcN550zjttK9z9tmfKcj1Qqrv7O0eUSmP/n+P7nbP87Vr15Kvgo85M7PlwIvu/pUBXl8AfNHd\njzKzQ4BL3X2bGwI05kxEZPRpPJxIYUR2zJmZHQZ8Aug0s3bAgfOBWYC7+y/cfaWZLTCzJ4DXgLMK\nWSYREXlHOd81LFKpCvonkbvf5+7buXutu8fdfX93/727X+Huv8g67hx338vd93P3hwpZpnLTtzk8\nFIo7LIo7LIo7LKHGnQ+1V4uIBGy0JxQWkfxpbU0RkcD1rPvZe5qPa7Tup0ge8hlzpuRMREQ0obDI\nKNPC5xUs1L56xR0WxV16PRMK19XVFTwxi1LcxaS4JVdKzkREREQiRN2aIiIiIqNM3ZoiIiIiFULJ\nWcSF2levuMOiuMOiuMMSatz5UHImIiIiEiEacyYiIiIyyjTmTERERKRCKDmLuFD76hV3WBR3WBR3\nWEKNOx9KzkREREQiRGPOREREREaZxpyJiIiIVAglZxEXal+94g6L4g6L4g5LqHHnQ8mZiIiISIRo\nzJmIiIjIKNOYMxEREZEKoeQs4kLtq1fcYVHcYVHcYQk17nwoORMRERGJEI05ExERERllGnMmIiIi\nUiGUnEVcqH31ijssijssijssocadDyVnIiIiIhGiMWciIiIio0xjzkREREQqhJKziAu1r15xh0Vx\nh0VxhyXUuPOh5ExEREQkQjTmTETKQiqVor29HYB4PE4spr8tRSS6NOZMRCpaZ2c7iUQdLS3zaGmZ\nRyJRR2dne6mLJSJSEErOIi7UvnrFHZbB4k6lUjQ1nU0i0cHcuVuYO3cLiUQHTU1nk0qlilfIAlB9\nh0VxS66UnIlIpLW3t1NT00V2L2YsBtXVXZluThGRSqIxZyISaclkkpaWecydu6XX/ra2sSxYsIq6\nuroSlUxEZGAacyYiFSsej9PVVUN2D2YqBWvW1BCPx0tXMBGRAlFyFnGh9tUr7rAMFncsFqOhYRnN\nzbW0tY2lrW0szc370dCwrOzv2FR9h0VxS662L3UBRESGMnt2nObmpKbSEJEgaMyZiIiIyCjTmDMR\nERGRClHQ5MzMrjazDWb2lwFen29mr5jZQ+nHBYUsTzkKta9ecYdFcYdFcYcl1LjzUeiWs2uAI4Y4\nZpW7759+fLvA5Sk7HR0dpS5CSSjusCjusCjusIQadz4Kmpy5+x+Bl4c4bET9saF45ZVXSl2EklDc\nYVHcYVHcYQk17nxEYczZoWbWYWZ3mNk+pS6MiIiISCmVeiqNJDDT3beY2ZHAbUBNicsUKWvXri11\nEUpCcYdFcYdFcYcl1LjzUfCpNMxsFvBbd983h2OfBurc/aV+XtM8GiIiIlI2RjqVRjFazowBxpWZ\n2VR335B+fhDdyeI2iRmMPEARERGRclLQ5MzMbgDqgZ3N7BlgMfAuwN39F8BJZvZ54C3gdeDUQpZH\nREREJOrKZoUAERERkRBE4W7NXszsY2b2mJl1mdnXBzjmMjNbk77Ls7bYZSyEoeKuxAl7h5qkOH1M\nJdZ1kJMzm9l0M7vbzP7HzDrN7EsDHFdRdZ5L3JVY52a2o5ndb2bt6dgvGeC4SqvvIeOuxPruYWax\ndEwrBni9ouq7x2Bxj6i+3T0yD7qTxSeAWcAOQAfwvj7HHAnckX5+MPCnUpe7SHHPB1aUuqyjHPdc\noBb4ywCvV1xd5xh3xdV1Oq5/AmrTz8cDjwfy/zuXuCu1zsem/90O+BNwWKXXd45xV2R9p2NbBFzX\nX3yVWt85xD3s+o5ay9lBwBp3X+fubwE3Acf2OeZYYDmAu98PTDSzqcUt5qjLJW6osAl7fehJiiux\nrnOJGyqsrgHc/QV370g/3ww8Cuze57CKq/Mc44bKrPMt6ac70v1HaN+f+4qrb8gpbqjA+jaz6cAC\n4KoBDqnI+s4hbhhmfUctOdsdWJ+1/Szb/hLre8xf+zmm3OQSN4Q3YW8l1nWuKrquzayK7tbD+/u8\nVNF1PkjcUIF1nu7qaQdeAFrd/ZE+h1RkfecQN1RgfQM/AhqAgQazV2R9M3TcMMz6jlpyJgPrmbC3\nFvgJ3RP2SmWq6Lo2s/HAfwJfTrckBWGIuCuyzt095e5xYDowz8zml7pMxZBD3BVX32Z2FLAh3Uo8\n4BRalSbHuIdd31FLzv4KzMzanp7e1/eYGUMcU26GjNvdN/c0lbt7C7CDmU0pXhFLohLrekiVXNdm\ntj3dCcov3f32fg6pyDofKu5KrnMAd98I3AEc0OeliqzvHgPFXaH1fRjwcTN7CrgRONzMlvc5phLr\ne8i4R1LfUUvOHgT2MrNZZvYu4DSg750PK4AzAczsEOAVT09kW8aGjDu7X96GmLC3zAz2F1Yl1nWP\nQSdnznpeSXUNsAx4xN2XDvB6pdb5oHFXYp2b2S5mNjH9fAzwEbpvdspWcfWdS9yVWN/ufr67z3T3\nPen+Drvb3c/sc1jF1XcucY+kvku9tmYv7r7VzM4B7qQ7cbza3R81s8+RnrjW3Vea2QIzewJ4DTir\nlGUeDbnETQVO2GtDTFJciXUN4U7ObGaHAZ8AOtPjcRw4n+67lCu2znOJm8qs82nAtWZmdP9e+6W7\n31Xpv8/JIW4qs777FUB99yvf+tYktCIiIiIRErVuTREREZGgKTkTERERiRAlZyIiIiIRouRMRERE\nJEKUnImIiIhEiJIzERERkQhRciYio8bMpprZjWa2xsweNLPfmdlegxw/y8w6i1zGL6bLt7W/WbrN\nbIyZvZhebil7/2/M7ORhXGeamf1qiGPmm9lvB3jt6QqYNV5ERkDJmYiMpt/QPUN2tbsfCJwHTB3i\nPcWebPGPwIeBdf296O6vA78Hju/ZZ2YT6F6mpd9Eqi8z287dn3f3U3I4fKD4NQmlSKCUnInIqDCz\nw4E33f3Knn3u3unu96VfbzKzTjP7s5ltk7SY2afM7MdZ2781s3np55vM7D/M7GEzu9PMDjazVjN7\nwsyOznr/r82sxcweN7Pv9VdOd/+zuz/D4Asz3wQszNo+HviDu//DzA40s/9rZkkz+6OZVWdd/3Yz\nuwv47+xWwfTzVWa2Ov04JOvcE9MtjI+Z2c+yP5Ksz+ITZna/mT1kZj9Pzz4vIhVKyZmIjJYPAMn+\nXjCzE4B93X023WsNNmWvN5dloNaiccB/u/sHgM3AxcCHgBOAb2Udtx9wMrAvcKqZ7T6SQIA/AHEz\nm5zePo3uRY0BHgXmunsd3UtvfSfrfXHgBHc/vE88/wv8i7sfkD7Xj7PecyDwRWBvutfYPSG7IGb2\nPrqXe5nj7vsDKbqXgxKRChWptTVFpGLNJZ3cuPv/mlkr3UlJruPN3nD3O9PPO4F/uHsq3TI1K+u4\nu9x9M4CZPZJ+7a/DLay7v2VmK+heE+9WoJbuhA1gErA83WLm9P49+l/u/mo/p9wBuMLMaoGtQHXW\naw+4+7p0mW+k+7O6Nev1DwP7Aw+mW8zeDZT1YtEiMjglZyIyWv4HOCnHY/vrlnub3q357856/lbW\n8xTwBnSvKmxm2b/H3sh6vpXBf8cNNabrJuDCdJlud/et6f3fontc3QlmNgu4J+s9rw1wrkXAC+6+\nr5ltR/fixwOVo++2Ade6+zeHKK+IVAh1a4rIqHD3u4F3mdmne/aZ2Wwzmwu00d3NGDOzXYEPAg/0\nHJb+dy1Qa91mAAdlnX6wMVYjHX9lQ7y3le4Wri/wTpcmwATeaY07K8drTQSeTz8/E9gu67WD02PS\nYnR3X7b1ee9ddLfg7QpgZpPNbGaO1xWRMqTkTERG0/HAR9ID9TuBS4Dn3f03dHdH/hn4b6DB3f83\n/R4HSN84sJbuFrhL6T1+bbBWrmHd7Whm/2Zm64HdgT+b2S/6fbO7A/8JTHH3e7NeagK+a2ZJcv8d\n+jMgYWbtQA29W9geAH5Cd9xPuvtt2eV390eBC4A7zezPwJ3AP+V4XREpQ9b9+0dEREREokAtZyIi\nIiIRouRMREREJEKUnImIiIhEiJIzERERkQhRciYiIiISIUrORERERCJEyZmIiIhIhCg5ExEREYmQ\n/wcN2SVNDGItcgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1161d27d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plotData():\n",
    "    plt.figure(figsize=(10,6))\n",
    "    plt.plot(pos[:,0],pos[:,1],'k+',label='Positive Sample')\n",
    "    plt.plot(neg[:,0],neg[:,1],'yo',label='Negative Sample')\n",
    "    plt.xlabel('Column 1 Variable')\n",
    "    plt.ylabel('Column 2 Variable')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    \n",
    "plotData()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "#Function to draw the SVM boundary\n",
    "def plotBoundary(my_svm, xmin, xmax, ymin, ymax):\n",
    "    \"\"\"\n",
    "    Function to plot the decision boundary for a trained SVM\n",
    "    It works by making a grid of x1 (\"xvals\") and x2 (\"yvals\") points,\n",
    "    And for each, computing whether the SVM classifies that point as\n",
    "    True or False. Then, a contour is drawn with a built-in pyplot function.\n",
    "    \"\"\"\n",
    "    xvals = np.linspace(xmin,xmax,100)\n",
    "    yvals = np.linspace(ymin,ymax,100)\n",
    "    zvals = np.zeros((len(xvals),len(yvals)))\n",
    "    for i in xrange(len(xvals)):\n",
    "        for j in xrange(len(yvals)):\n",
    "            zvals[i][j] = float(my_svm.predict(np.array([xvals[i],yvals[j]])))\n",
    "    zvals = zvals.transpose()\n",
    "\n",
    "    u, v = np.meshgrid( xvals, yvals )\n",
    "    mycontour = plt.contour( xvals, yvals, zvals, [0])\n",
    "    plt.title(\"Decision Boundary\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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VynjssStx++0dMXnyGowbt6rIe3755Tguv7wZZszohxYtagcgyopj1r8ujca8rYV5W0uw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\nxMWZmZmZWYq4ODMzMzNLkf8HT9bzutbvpacAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1161d26d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Run the SVM training (with C = 1) using SVM software. \n",
    "# When C = 1, you should find that the SVM puts the decision boundary \n",
    "# in the gap between the two datasets and misclassifies the data point on the far left\n",
    "\n",
    "#First we make an instance of an SVM with C=1 and 'linear' kernel\n",
    "linear_svm = svm.SVC(C=1, kernel='linear')\n",
    "#Now we fit the SVM to our X matrix (no bias unit)\n",
    "linear_svm.fit( X, y.flatten() )\n",
    "#Now we plot the decision boundary\n",
    "plotData()\n",
    "plotBoundary(linear_svm,0,4.5,1.5,5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Jcy7JOdfMzH4ufuIrr5zPvHnfcvXVc3nqqWwmTDiNNm0ahDR+EZF4pVHuItEp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\nPqJosf37ti9vuf9Z2+PZ7QO2/8b2N2zfavtc23ts32f7VS3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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1164e7e90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# When C = 100, you should find that the SVM now classifies every \n",
    "# single example correctly, but has a decision boundary that does \n",
    "# not appear to be a natural fit for the data.\n",
    "linear_svm = svm.SVC(C=100, kernel='linear')\n",
    "linear_svm.fit( X, y.flatten() )\n",
    "plotData()\n",
    "plotBoundary(linear_svm,0,4.5,1.5,5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#help(linear_svm)\n",
    "#linear_svm.get_params()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.2 SVM with Gaussian Kernels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 1.2.1 Gaussian Kernel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.324652467358\n"
     ]
    }
   ],
   "source": [
    "# Here's how to use this SVM software with a custom kernel:\n",
    "# http://scikit-learn.org/stable/auto_examples/svm/plot_custom_kernel.html\n",
    "def gaussKernel(x1, x2, sigma):\n",
    "    sigmasquared = np.power(sigma,2)\n",
    "    return np.exp(-(x1-x2).T.dot(x1-x2)/(2*sigmasquared))\n",
    "\n",
    "# x1 = [1 2 1]; x2 = [0 4 -1]; sigma = 2;\n",
    "# sim = gaussianKernel(x1, x2, sigma);\n",
    "# this value should be about 0.324652\n",
    "print gaussKernel(np.array([1, 2, 1]),np.array([0, 4, -1]), 2.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Now that I've shown I can implement a gaussian Kernel,\n",
    "# I will use the of-course built-in gaussian kernel in my SVM software\n",
    "# because it's certainly more optimized than mine.\n",
    "# It is called 'rbf' and instead of dividing by sigmasquared,\n",
    "# it multiplies by 'gamma'. As long as I set gamma = sigma^(-2),\n",
    "# it will work just the same."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 1.2.2 Example Dataset 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "datafile = 'data/ex6data2.mat'\n",
    "mat = scipy.io.loadmat( datafile )\n",
    "#Training set\n",
    "X, y = mat['X'], mat['y']\n",
    "\n",
    "#Divide the sample into two: ones with positive classification, one with null classification\n",
    "pos = np.array([X[i] for i in xrange(X.shape[0]) if y[i] == 1])\n",
    "neg = np.array([X[i] for i in xrange(X.shape[0]) if y[i] == 0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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MmpubG/r8gQceoN26daNt27alAwYMoNu3b6eUUrpp0ybatGlT2rRpU9q6dWualZVFKaU0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\nYdTU3Kk55RycpuQ37RLrvilTV2phmZoa/F15eQVmzhyLv/9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XzDSp5QAmW94yIvoUgF8C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\nxwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1166aebd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotData()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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XZxxdcPeeFYSXsNQ0ekuv2mFXVqJUyjClkrj83WdWUa2FOPO2KENJfJ6G0Fkw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zC9h5G0h0YydcqdELXSAhiFALDGtWuViI6+gxkxYwGpOcgaQv/JAetIXpqaJ6n9JySddrsdhYWT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\nDMMwjBBh4swwDMMwDCNE/D9/lR2CZ+ziqwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116a15f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Train the SVM with the Gaussian kernel on this dataset.\n",
    "sigma = 0.1\n",
    "gamma = np.power(sigma,-2.)\n",
    "gaus_svm = svm.SVC(C=1, kernel='rbf', gamma=gamma)\n",
    "gaus_svm.fit( X, y.flatten() )\n",
    "plotData()\n",
    "plotBoundary(gaus_svm,0,1,.4,1.0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 1.2.3 Example Dataset 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "datafile = 'data/ex6data3.mat'\n",
    "mat = scipy.io.loadmat( datafile )\n",
    "#Training set\n",
    "X, y = mat['X'], mat['y']\n",
    "Xval, yval = mat['Xval'], mat['yval']\n",
    "\n",
    "#Divide the sample into two: ones with positive classification, one with null classification\n",
    "pos = np.array([X[i] for i in xrange(X.shape[0]) if y[i] == 1])\n",
    "neg = np.array([X[i] for i in xrange(X.shape[0]) if y[i] == 0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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8CPHDyltOn+9iEw7T480vUs5yc6oOLttkHt4jmfyuOZsOYIOqbgIAEbkbwBwA\nqeRMVZ9M2/9JAPt7WkLyFGsIzOV3cmY6p79IMdlzhxfLNrndZOp3k6zfrx8Gfp/R/QFsTtvegoGT\nr28CaHa1RAbjG3KmMI9eDeOxZzvmIJ+H+vp6NDY2orGxEQ0NDamfw/I+YGtsu7o6EI3WoLm5Ds3N\ndYhGa9DV1WHN8/v1+rbG2y1+15wVTERmAjgfQK3fZfFLUN+UWUNQPFtrnZyOtVvnodyaARtjExZu\nruHpdpOp302yfr9+mPidnL0C4IC07fGJxzKIyFQAtwA4WVXfGugJo9EoKioqAAAjR45EVVVV6o0y\n+aHAbfO26+vr0dLSgp6enlRzUPKDPNffJx8zofzcLnw7Gd+enp5U7Av5++Rj6b/v6enJ+J0T5dt7\n7xFYvPgC7L77OgDAxx9PwYIFK/DGG+8U/HzJ69mJ8rjxfG5tx2IxjBgxAgDwzjvvIBKJlPx8ycfc\nKO+CBStw2WVnYfz4LZg0aRA2bJiM+vpvobW1taznf+GFF1JNpp2d8WOoqoo3mS5btgyHHHKI0c/v\n5+snHzPpenZjO/lz+ntXNr4u3yQigwC8gPiAgG0AngIwT1XXpe1zAIDHAMzv0/8s2/Nx+SbLJZtu\nqL+WRLIKxGudGhoaAJRe6+S3UmPt5nmIxWKIRmsyagZiMaCpqYo1A3n0HQHZ3W32CEg3+k21t7ej\nubkOtbXvZzze1jYEs2a1lt2fze3nN/31gyjX8k2+1pypaq+IXAzgUXw6lcY6Ebko/mu9BcCVAEYD\n+JWICICPVXW6f6UmNxXz4Zr+LSss0pMZ25PYYmOXjHffJMzJ8+BFZ/EgcqO5y+37O7lsk5PcbDL1\n4vn9fP0wvp8PxO9mTajqwwAO6fPYb9J+vhDAhV6Xi/zBmzO3oL15BelYwo5JbVwkEsGCBSuwePEF\nmDw5XoO4YcNkLFiwwpGaOaeev9RaQ7ePjz7le3JGVKowf7iH8dizHbPT58Hvmgn6lK3X+GGHVaOp\nqd21qSbKff5yJ+B16/hsjbdbfO1z5jT2OaOgCVo/MxskP7wyawZuM7bvlAnYV88OjJN5cvU5Y3JG\nrnOrOc6kZj4vyhL2wRJexpuTbBbP6aQ2W7wZl/KY3KHfpPdzLxk5IIDCIQw3XRiOMUzc6CwedG43\n53E9TAoTfu0ga4UtGQrb8fYV9uO3QTKprampKTsxS493+mjQ2tr3UVv7PqLR+GjQWCxWZqnDo7q6\nGt3dlUiKM6ieAAAgAElEQVQ/Zab0qeT9nYk1Z+SKvn2lkoLUV8rrYwzKeSMqFkeDOoOjLe3B5Ixc\n4eZcVEl+NyV6cYym8uPc+x3voDPt/JpWnqBwu/m5VIx3Jv8jQkTWSV+KhILB5Jia3BxnIyebn8kd\njAq5zq1vQyZ9yzKpLEHFc5ybyYlVqdLjnWyOa2qqQlvbELS1DUFT0zQ2xwUI7+9MbNYk15lw07ld\nZW7CMbotDP0IbVXq9W1TTE1tjiNyA5MzslYxH0jsz1A+v/vY+RnDoF4/fsd0INnOOac4Ca6g3mOl\nYnJGRJSHiR8cNtV6hREnzKVyMDkja+X7AOKHl3v8OH+MWSana71MO7+mlacYnDC3eDbH2w2BTM5M\n/JZL3jO5ycZ2Ybi/wpbcB/GY/JA+YW6ysmzGjPiEuVy/kgrF5IysxTiHi9fxtim5D+J9YOv9zQlz\nS2NrvN3CFJ5CgTc9BRmvb6JgEVX1uwyOERFtaGjAokWL0NDQACC4TRBEXuC32TieBypULBZDNFqT\n0awZiwFNTVVs1qR+RASqKn0fD1yzZrLpweQmCCJbMCmJ4zmgQnH9SnICrxSyVhBnRafcGO9wsTne\nyQlzZ81qxaxZrWhqepojNfOwOd5uCFzNGcBvuUTlCNsoRaextpEA5ybM5Xxp4RS4PmdBOh4ivzU2\nNlrdRcCPRMn2c0bm6DtfWnc350sLmlx9zpiCE1FgsamkcLFYDO3t7Whvb0csFvO7OKGXPl9abe37\nqK19H9FofL40xif4mJxZxM0PGhs/xGwss21Map4zOd4tLS2pGrNFixalfja5zOm6ujoQjdagubkO\nzc11iEZr0NXV4WuZbDl3bsk3X1rQhD3efeXtcyYiAuBrAA5U1atF5AAAn1XVp1wvHWVws4mG/WQo\nGxuvCTf6zOW7P2yasLavMMxoz35bZJtCBgT8CkAMwPEArgbwLoDfAzjSxXIR5WVj4kClKzTebiRK\nQf7y4uSM9k6eJ6eex9Z1Lqurq7FkSSVmzMicL23DhkpUV5dWdpOT1KDeX6UqJDk7SlUPF5EOAFDV\nt0TkMy6XixLcHDnHUXlEzgvzvWNaEmtzraDT86XZmqSGVSHJ2cciMgiAAoCI7IN4TRp5wM3mEpub\nYgDzPgjCyqs4lPI65ZSr1C8vtl2TbtTQOMGJ68r2dS6T86WVW9tlQ5LK9/NMhSRnSwH8AcC+IvJj\nAF8FcIWrpSIio6W/kZr8plpOubz68uL3+Su3hoY18O5yYr4025PUMMqbnKnqnSLSDuAEAALgdFVd\n53rJqB833+hsfBO1scxB4UdCEdR4+52cAeXV0LiVxDpxTkytFaT+/L4HTJMzOROR0WmbrwFYlf47\nVX3TzYJRf0zOyBQ9PT2pD+Ew1JYE8Zj6cmpGe5Nwncs4Jqn2yblCgIi8hHg/s34z1wJQVT3QzYKV\ngisEhIsJNQ7ZmFquvootZ9/mq4aGBgDxRK2pqcn5AmZ5fRvOayFynUvbk1snY+Tkc5k8StEryQEB\nmUnqbcYMCAjS/V2MXCsE5Kw5U9VJ7haJKJhseZMptpy5mq9sG0hiAtsH4+Ri6nUfxFrBYjk1uIC8\nUdDC5yJyJoBaxGvS2lT1fldLRVQAUz8IwsarODDe4cJ4O8/kJJXxzlTICgG/AnAwPu1z9i8icqKq\nftvVkhE5wMtpHmwYseZUOdP3Nen4bMTzR0R95exzltpBZD2AKcnOXCISAfB3VZ3iQfmKwj5n4VJI\n4pVc49BLfrxmKUwuZ7bY2tJcTM5gvMMlrPHO1eeskAbn/wVwQNr2hMRjRESu4CLI5IVYLIb29na0\nt7cjFuPc6mSOgabS+C/E+5gNA7BORJ5KbB8FgIuek+9yfcvyu4nRlm9/tpQzybby+iUoIxPdjjeX\nMzIL7+9MA02lcdxAf6iqT7hSojKY1qwZ1mpak5jcdEeZgjq9hJf6Jhzd3Uw4sonFYohGazKWM4rF\ngKamKmOWM6JwKGUqDeOSL9uEOTnz4tjDfH6DKN/0Eoz3wGxYPzGXbLV9bsabyxmZh/d3prx3q4gc\nLSJrRGSniOwSkV4R2eFUAUTkZBFZLyLdInJ5jn2WisgGEekUkSqnXpvcY0qfId7s2ZkSH3JOvoTD\nVF1dHYhGa9DcXIfm5jpEozXo6jK3vEReKGSes5sAnAPgXgBHAPgGgEonXjwx8vMmxNft3ApgjYg8\noKrr0/Y5BcBBqjpZRI4C8GsARzvx+m7wu79TmBRyPnnOszP9W2q2splcXipNvto+t3A5I/Pw/s5U\n0CS0qvq/IjJIVXsB3CYiHQAWOvD60wFsUNVNACAidwOYA2B92j5zANyeKMffRGSEiIxV1e0OvL7j\ngjrzdyGYmJJTeL0Uz8aEw6/mxaCtuWn6ly0qXiHJ2fsi8hkAnSLyHwC2obApOAqxP4DNadtbEE/Y\nBtrnlcRjRiZnYeZ1Yso3pOLYnjwz3gMLWsKxdu1aV/t+BWk5oyDcG0E4BicVkpzNBzAIwMUALkV8\nnrOvuFmockSjUVRUVAAARo4ciaqqqlTAkx9MXm2PHDky44Lz+vWDvt3Z2WlUeUzfTv6c3O77v9/l\nMy3eN954o6/vH6VuJxOOtWvX4phjJqdGaqbvH4vFsGzZMgDAhRdemOqA73V5Y7EYurvjtX3PPgsA\nwNSp8dq+oUPfQwvfP0OzHZb38+TPPT09GEjeFQLcJCJHA2hU1ZMT298HoKp6fdo+vwawWlXvSWyv\nB3BctmZN06bSCLP0N1UyD6cYyS+o58i06TaS5cms7buN03/k0dLSkvrA59Qz9ip6Kg0R+a2qni0i\nXYhPPptBVac6UK41AA4WkYmIN5eeA2Ben30eBPBtAPckkrm3Te1vRp/im4PZGJ9wMnG6jSA1L3qp\nbxLmxReJoExwbIOBmjUvSfx/mlsvrqq9InIxgEcR78e2XFXXichF8V/rLar6kIjMEpH/BfAegPPd\nKg/ZhbVzpbPxvHkR7761EUlBqY0wdX6vSCTS77V5f5vF7RUVGO9MA01Cu01EBgFoUtWZbhVAVR8G\ncEifx37TZ/tit16fiCjJj9oIonK5ndSYWOMadAOe0cTUGTERGeFReagE6R0Nw8TWb1lhjVe5bI23\nSaqrq9HdXYn0Nb5NnW6D8S6c2+fKiwmOGe9MhaS7OwF0icjyxEz9S0VkqdsFo8Lxw94uQYhXEI4h\nnyB+WCSn22hqqkJb2xC0tQ1BU9M0a6fbIAqqQu7G+wBcCaAVQHvaPyJfhSFBMJUf5z7fazpdpiAm\nZ8CnHfBnzWrFrFmtaGp62siRkby/zeFFjSvjnSnvPGequtKLglBxgt5xOWgYL/c50aE4LJ2Ss3XA\nJ8rFxAmOnR45atpI1LzJmYhMBvATAIcC2DP5uKoe6GK5KA92XLarZiMI8fI7wfTiNYpJzsKSyDmp\nmA9AnluzuD3lSTHxdnrkqNsjUUtRyAoBtwFoAPBzADMRn8qCnROIQsbEBNPPhJHJWXFM/ACk4phQ\n4+r0yFFTR6IWkpwNVtXHJD79/iYAjSLSDuAql8tGBQrrB4StH442ltkE2eLtRMLod41gGJTyAWjr\n/U2lKTTeTs/VZ+rcf4UkZx+JSATAhsSEsa8A2MvdYlEx+AZmlyDEKwjHkFRMgsdErjSmfgASmaqQ\n5OwSAEMAfAfANYg3bZ7nZqGICsEPQ//4ce7zvaZX/d5Ma9oNKt7f5nVSd1Oh8a6ursaSJZWYMePT\nWthyRo46/XxOyRlpETlLRPZU1TWqulNVt6jq+ar6FVV90stCUvhwWDUVy4kPcyYE7rBp8ttcYrEY\n2tvb0d7ejlj6gbikq6sD0WgNmpvr0Nxch2i0Bl1dzkz4ajOn5+ozde4/Ue23pnn8FyJ/AHAMgEcA\nrALwSGLFAGPFu8VlPx6yS2NjY95aCfZJCRfT4m1aeUyXHBCQORXDbTkHBJh0fvsOZujudncwQywW\nQzRak9FHLxYDmpqqArtcUrHxDspUGiICVZW+jw+0tuYZIjIcwBkA/g3AchF5AMAqVX3CvaISUVCZ\n9IFbrqAch1fcnorBLX6M5mMfvfycHjlqwkjUdAP2OVPVHQBWAlgpInsD+CqApSIyWlUneFFACo9i\nO1vzw9E+5SRnQY2319/Y/ezHVMwHoCnxLjdRClO/MaD04zUl3qYoZEAARGQUgDMBzAUwGsDv3CwU\nhRM7W3srSLVYtvJ67i/ONeatUs+3qZ3U8+H15ZycyZmI7IV4k+Y8ANUAHkR8tGYLO3aRCQpJLpiA\n5ObVuXFq+omgxdLr5jJTJ9vMxZR4l5oolXO+TVwuKZ9yry9T4m2KgWrOegA8DOBXiA8G+NiTEhHB\nuSpu3vD+Y41odl73K2I/ptKUmiiVe75t66PH68tZAyVnE1T1A89KQpSmkIQqzElXqUmnzZOoml4+\ncpZJ8fYrUTKtk7qbTIq3CQYarcnEjKxkcwJSqFKTM79rsYJy/p3gdb8iW/sxmaLYRCls5ztsx+u2\nggYEEJkoV4LidwJCuZWTnAWtidrrfkW29WOyPd62ne9ylXu8tsfbaUzOiCzhdI0g3wj953VzmW39\nmGwXtvMdtuN100ArBAwC8E0A4wE8rKp/TfvdFar6I2+KWDiuEEB9BfXbWCErKBARkdlyrRAwUEr7\nGwDHAXgD8Ylnf5b2uzMdLh+RK4KYmBERUbANlJxNV9VzVfVGAEcB2EtE7hORPQD0y/KIvBbmxdFt\nSDqdXijarXh7vaA1FSbM93cYMd6ZBkrOPpP8QVU/UdV/BtAJ4HEAe7ldMBoYL+RwMz056+rqQDRa\ng+bmOjQ31yEarUFXV4ffxerHq3Lyfi0NzxuF1UDJ2VoROTn9AVW9GsBtACrcLBTlxzct8xMUN5lc\n25M+U3ht7fuorX0f0Wh8pvByyup0vN0qZza8X4tXX1/P8xYiYX4/zyZncqaqX1fVh7M8fquq7u5u\nsYj8ZfKHgum1UvlmCjeFLeUkovDhVBoWCcPkqsVwcySmqaM8bVsf0UmmxiQX3q+lSZ63np4erFy5\nMvU4z1uw2XZ/u43JmUWKmVyVF3ow2bB+nS0zhbtdTk6GXJrkeWtpaUFFRQXPG4USk7OACkNy5vTx\nsabDGW7NjO50DMI2g7tt2OcsXPgem6mg5ExE9gcwMX1/VW11q1CUHy9k59lQ02FLrZQtM4V7VU7e\nr6XhefNPLBYz/v4NsrzJmYhcD2AugOcB9CYeVgBMznyU7U3L5pqfUt4IwlA72JdNtT3FLhSdj1vx\ndrqc2YTtOnVCGO9vU3R1dWDx4gtQWRl/j1mypBILFqzAYYe59wWQ8c5USM3Z6QAOUdWP3C4MlceG\nmp9s/HgjyMfkNwlbaqXIDKwBoWI4OeiI117pcq6tmdpBpBnAWaq605silY5ra37KlrUXY7EYotGa\njDeCWAxoaqoK/OhDIrf1/eLT3e3fFx9+UNuhvb0dzc11qK19P+PxtrYhmDWrteBaZpOuPZPlWluz\nkJqz9wF0ishjAFK1Z6r6HQfLRw4zueYnnQ2jD4lsZNK0KybWjpN7TLr23OL2l41Cnu1BANcA+B8A\n7Wn/yCVOjFCyJTkrB0dyhYuT8TZ5hQWnmDLJbqkrMfD+9kd1dTW6uyuRHppiBx2Vcu3ZFG8vJgLP\nm5yp6sps/xwtBWWw6SItlxNvBETFMH2FhaAxJUmkwiQHHTU1VaGtbQja2oagqWmakYOO/ODVsm95\nz7SInCYiHSLypojsEJF3RWSHYyWgUCvnjSBItYNhSshL5US8vVxP02+2f/EJ0v1tm+Sgo1mzWjFr\nViuamp4uqgm6lGvPlnh79WWjkD5nNwI4E0AXe9u7x+ZpMMrF0YfmDyM3vXyFClMfR1OmXbFlbj7K\nVM4UM6ZcezYrJDnbAuA5JmbusnUaDKeU8kYQlITBBiacaxPKYBsTvviU+kFdaLw5CtRMxV57Tt3f\nbl8PXn3ZKCQ5uxxAs4i0IHO05s/KeWERGQXgHsRXHugBcLaqvtNnn/EAbgcwFkAMwDJVXVrO6xKZ\nIsy1pX4JYy2OF5Ps5uNWkshRoGbz+trz4nrwqlawkHnOHgWwE0AX4gkSAEBVF+X8o0JeOL7ywBuq\n+h8icjmAUar6/T77fBbAZ1W1U0T2QnyU6BxVXZ/jOQNRwccagvAxcV66vsljQ0MDAPuTx+QbeOYb\n6238QLcM50ikdF5fD07V0JUzz9l+qvqFkl51YHMAHJf4eSWAFgAZyZmqvgrg1cTPO0VkHYD9AWRN\nzoLC5g8+Co6gNrWb0NRH5QtT/0HKz8nroZDEy+1awULekR4SkZNceO19VXU7kErC9h1oZxGpAFAF\n4G8ulIUs5PUIRzdfr5yEPCwjPZ08zuQba01NDRMzQ4XluqY4U+JtylQ7hdSc/SuA74nIRwA+BiAA\nVFWH5/tDEflvxPuLpR5CfNH0K7LsnrM9MtGk+TsAl+RbRioajaKiogIAMHLkSFRVVaU++JLB53Yw\ntjs7Oz19vaamJteev76+vuS/TzaDu3n8bj9/Idtex5vb/m7ni/c777yD1tZxmDFjIyIRoLMzs/+g\nV+Wtq6tDR0cH1q5di8mTJ+P444/35XzZvl3u/e3E9RCLxdDUdBmi0U48+ywAIDXVTjR6AyKRSNnH\nm/y5p6cHA8nb58wtiSbKelXdnuhbtlpVp2TZbzcAfwTQrKpL8jxnIPqckZlM7BcGmFsuCh7TRkb6\n3X/QpPUjTYuNH8q9HpxaV7QYJfc5E5G6bI+ramuZZXoQQBTA9QDOA/BAjv1WAHg+X2JG5IaWlpbU\nNx6TRlSaWi4KLhNHRvrZf9Ck9SNNjE2hnEwqg9SftJDRmv+VtrkngOkA2lX1+LJeWGQ0gN8CmABg\nE+JTabwtIuMQnzLjNBE5BkAr4iNFNfHvB6r6cI7nZM1ZiLQkmvO8YmoNlanlcprX8aZP+TEy0vR4\n+1HLko3No1bTk8qXXurFxx9P8TWp9ONcllxzpqqz+zzRBMRXDSiLqr4J4EtZHt8G4LTEz38FMKjc\n1yIynekfRH5J/1YdtOWVbMKRkeayNTZ9ax732guYOtWfmsckk1Y2KGRAQF9bAPTrG0bkNa+TGTdf\nr5zkLKhJXbb+PPvsY0dTDZXP9Os6jBMaO6lvUllVFf/f76TSlKbRvK8oIr8QkaWJfzcBaAPwtPtF\nIzKLqR8WpparHDYvUJ4+KisobF9E3Q3JWpampiq0tQ1BW9sQNDVN82XtUsbGWSZMtVNIzdnatJ8/\nAbAq0dxI5CvbmwLZqT+3bE01zz7r/7fqQth+XWbjR3OPDefRhFoWk5riitG35rGzE5g6lUllUiF9\nzlZ6URCisOmbhIWhUz/Zy4RExERBXrvUTX2Typde6sXTT3/O+KTSKzmTMxFJjpDs9yvEJ6Gd6lqp\niApg+rdqKl22/jxTpwJNTWZ+qw5LLaiXiUiQzpsXTEgSi2VjUumVnFNpiMjEgf5QVTe5UqIycCoN\nspUNTTheT3Lp9wSjpQrL1CZEVL5cU2nkfHdV1U3JfwA+BHBY4t8HJiZmFD5B6nhtemLmx3pzyW/V\ns2a1YtasVkSjPzM+MSPnBOn+pvwY70yFjNY8G8BTAM4CcDaAv4nIV90uGBGZwc+RkyaMmiqW6Yl2\nUMRiMbS3t6O9vd34EbxExSpkhYBnAJyoqq8ltvcB8GdVneZB+YrCZk0i55kyEzpRkklrWhKVo+QV\nAgBEkolZwhsooMaNiIjIaSataRl2XGzdPYWcyYdF5BERiYpIFMCfADS7Wyyi/NhHwRumTHLJeIdL\nrnjnW66IvOF0P1Te35kKmedsgYicCaA28dAtqvoHd4tFRKawdZJLInIHay/dN9BUGgcDGNt3NQAR\nqQWwTVU3elC+orDPGZF72IRBJojFYohGazISg1gMaGqqYmLgEfZDdU4pfc5uBLAwy+PvJH4326Gy\nEZEFbJzkkoKHNbkUBgNdyWNVtavvg4nHKlwrEVGBnOyjwP4O5mOMnGHLFBQDxbvvHHhNTU9zpKaH\n3OiHGpb7u9D7b6Cas5ED/G5wySUjMpANM/RT4dgEm13fKSiWLLF3CgrW5PqHtZelyXb/5TJQn7NV\nAB5X1WV9Hv8m4vOezXWsxA5hnzMqFZfcCQ7b5sDyKpFkXy1yGr8EFSZZW9bY+HVcemk3dtst+Thw\nwgnI2udsoORsLIA/ANgFoD3x8BEAPgPgDFV91YVjKAuTMypG38WqGxoaAARvseowsS0B8TKRZCdu\nIu8l7/GDD16P3t4P0dUFzJ4NTJoU//3MmdmTs5zNmqq6HcAMEZkJ4AuJh/+kqo+7UH6iopXbFNk3\nCSu05ozfFv1RSLzzzYFlUgLC6QgGxq4G4dLS0oK6urpAvbdmu8ePOw646Sbg4ouBgQ4v75Gr6mpV\n/UXiHxMzCjU/FgC3lS0dz/3i9WSqpkwmTJTNiy9uCNx7a657fNo0YMMGYKC3RbvTUgo1J79VF/Jc\nbi0AHsQkxo0ktpAYMQHJLdmJu6mpCm1tQ9DWNgRNTdOM7cTNWrPwiMViaGn5lePvraaKxYDOzj3R\n1JR7ifK8C5/bhH3OyE1u9NmxrfN6Ifzu95U8p5mjyG4z7pz6dZ7YLG8GxuFTQe0Pmesev/nmSvzf\n/3sHampqMGjQoJIXPicyku19UoLa58itfl+Fxjs5B5bpH3x+TUdgyxQUtt/fAwnSlCZOeemlXtTW\n5t/PJrnu8auuyv9lkckZUYGqq6uxZEklZszI/BZUapOZTZ3XTZatBsKWBMSWRJKcE9QvZeWorq7G\n5s3jEYttdOS91SSl3uNMzshaXn+r5sSLhXE6iU3KFu8g1EDYkkh6Lai1ZvxS1l8kEsENN9wb2PfW\nUu5x9jkjKpJTfUX87pvlJi/6fQX5/FH5TO3TFdT+VU4wNWZuyrXwOZMzslYQ+qTY0nm9FE6/0faN\nNz/kgq2c+9vkgTb8UpFdEN7PS5ErOWOzJpGPgtzniM115AfT+3SxewQVgjVnRGQl1kBQNrbUqIax\nCY/6Y80ZBVZYq8PDjjUQZDM3a5aZ+NmPESNrJRctT/5PwZYtzslm4VmzWjFrViuamp42ol8Rla/U\n+zrsq0TYusQc38czseaMiKzGvm2ULsw1qqb3t6PCsc8ZWamlpSX1TWvRokVoaGgAEJ8biU2cRBTG\npj1b+ts5ISjxZZ8zCpS+SVhjY6NvZSEi87BGNbiCMPl0PnammmQNN/sRsI9CuIQt3rFYDO3t7Whv\nb0csvQNVSIQt3k6wub9dofFOb7qtrX0ftbXvIxqNN90G6T5hckau8uINls2YmcL+oR4EtnbqBnj9\n+SnZ366pqQptbUPQ1jYETU3TAtXfLt/yV0HBPmfkqsbGRjY5esjkmdGpMDbP38brzwxB6Y+VTdD6\n1bHPGXmmb2f9JHbWdxdHagWDrQtj8/ozR5D721VXV2PJkkrMmJH55cWGptti+JacicgoAPcAmAig\nB8DZqvpOjn0jANYC2KKqX/askFQSrzrrc/LZTLZ+qBeK8XZXubUtTl9/jHe4FBrvsEyV4ueRfB/A\nn1X1EACPA1g4wL6XAHjek1IRZcHOyeQVPzp129zHjcInDJNP+5mczQGwMvHzSgCnZ9tJRMYDmAXg\nVo/KRQ5y85uvl9+qbUjObB6pVYiw1KJ43anbqdFvTl9/YYk3xRUb72TTbU1NTaBqzJL87HO2r6pu\nBwBVfVVE9s2x388BLAAwwrOSkWP4BuudsFT3h0GyZsCLTt1ONUfy+qOg83KghavJmYj8N4Cx6Q8B\nUABXZNm93zBLETkVwHZV7RSR+sTfEwFwv0+KjQMbvPxQ95rffZC8HgFnY6duJ68/v+NN3jI93l5P\nfOtqcqaqJ+b6nYhsF5GxqrpdRD4L4LUsux0D4MsiMgvAYADDROR2Vf1GrueNRqOoqKgAAIwcORJV\nVVWpgCc/aLkdjO3Ozk5Xnz/5c3K77/9+H/9A2zU1NWhpaUFra6sR5XFi2+14D7Td1dWByy47CxMm\nbMGkSYOwZEkl6uu/hQMPnGzM+Sl1u66uDkuWVGLIkPjot6qqeHNkW9s4HHPMp2O0vL7+/Ip3XV0d\nOjo6sHbtWkyePBnHH3+8p68f1m0/7+9827FYDJdddhZOPnkjDj8cAIAhQzpx2WVn4eGHuxGJRAp+\nvuTPPT09GIhv85yJyPUA3lTV60XkcgCjVPX7A+x/HIDLBhqtyXnOyC2cry28bJ53rFDJWoHM5sjb\nAtfJOh/O00bZuDm3monznF0P4LcicgGATQDOBgARGQdgmaqe5mPZiDIkv/1Q+WybIDPoU5QA3jSH\nmx53ztNGJvHtalPVN1X1S6p6iKqepKpvJx7fli0xU9UnOMcZpUuvJnYbk7PiZVvGp5wpG7yMdxi5\nOfqtlLh7He8gLQtk4xJaJt/ffoyE51cBInJctg/jZ55pt3LB4qBPUeK2sCxUbQrOWec8P9Ys5dqa\nRD5qaWkJXK1crj5aN99cicMO24y6ug8y9rdhTTz2ySqdLWshBqFvYRCOwWRuNM2b2OeMyDemJEWm\nlMNJuZqHvvCFl7Ftm3/lKkeQpyihuCDM0xaG/pF+8nJ6GzuuOKIsyumjYHL/hqCKRCJ4+eUDSm4e\n9DtmQZ+R3C2lNgv7Ee8wLAtkKr/vb9Ow5ozIYy0tLak3Ilsmty1GdXU1liypxIwZmU0rGzZU4tpr\nb8UNN3zT2poJKp5tNVI2Tv6bNNC9x/6RdmGfMwqNvklRQ0MDAH+TonLnTzN1eoKB+miZWmZyF+Pu\nDfaPtEuuPmdMziiUTJlUtpxymD5hJj+MifwR1HsviMeVKzmz/8gotILQR6HUGjsbpidwuo9WEOJN\nhWO8S2dj/8h88Q7bFCF2RI3IYab07Sq1HEGaMJPsV+qkpzZOlkres+HLqNOYnJHRBvo2VU6CZUpy\nRoVjzMxUao1Gvr9jvMNloHiH8csokzMyGps2suOs9WSCUms0wlgTQlQMJmdkrTAnbn4sJ+K3XPFm\n06NJ4XEAABGeSURBVJh/Sq3RKOTvwnx/h9FA8Q7jl1HOc0bGCfo8YE7hrPX9R6wuWWLWiFWTmDLS\nLRaLYd26dXjllRhiMSBklyyVwLa58pzAqTTIaKZMeUHm4TqChXNr2pViY5Bejo8++gB//7ti9mxg\n0iTGjvIz5QuGk7i2JhEFCtcRLEx6/67kuZoxI96/q9xEqJgajWzlmDkTuP56wYwZe2LjxspA14RQ\n+WxevaFYvAvIaAM1Y7JPSrgw3qVxe6RboetR5irHjBl74KCDbun3d4x3uDDemZickdHYx4xyCXon\nYZsGOpQz6WkkEsGUKVNYY0aUhn3OiMhaQV1H0Mk+Yqb0zctXDgCB609ElA/X1qSUlpYW1khRYJjS\nSdipcriRTJmSxOYqBwCj14klcguTM0oJyghIJpnhYnK8nazpam9vR3NzHWpr3894vK1tCGbNai25\nQ7SpSSyArMnoddcdhIcf7i6qnKYco0lsOScm399u4sLnREQusGW2e1MWw+5bjlwDBcaP31LUgAUv\nF8a2pT9g2BYLDxJOpRESQZzYtZBye/ltzJZvqLYy9Tp1ekqP6upqLFlSiRkzMmuSgjLQoVCTJg0q\neF83pwvpy5aJj708J04w9f72C5OzkOibhAWhWbMQXiVntrxhk/nCNhu6E8moV3Pe2ZTwcB5Au5lz\nJREVyZR5cWxp1rKdKfHuy40pPQqdO8wJfjfR5Vontr7+W0YlO4D7c8aFman3t19YcxZCQa8+9roJ\nl99Qw82tmi4vZkM3pcY32zqxra2tBf89m4L74zmxG0drUqB5MTLVrdF1YWRzvz3bym7K/GdO8WK6\nENvOmSlTqFBuXFuTyCX8huoMU2pxSmXbun9Bq/HNVvvmdLJkW39AL84JuYPJGVmrkM7+XjTh2vaG\nbaJCOlqHdR6ksCol3l4kyLYlPLZ8aeD9nYnJGQWaVze7yW/YNjS3Ba0Wxwas8S2dLQkP2Yt9zogC\nzMmZ693EfnulKTfxZp8kIn9x+SaikLGp87JNZTWFU4m3DTWrhQrSsVA4cPkmChzOizMwm+ZkyjXX\nVXq/Pcb7U7nm1rv66nOwZs2aouYrM2VZp76KjTeXKrIb7+9M7HNGREYwud+eaXIl3oce2o0VK+rw\ni198zsjma7fYNHM/USF4xZK1OLJnYG7MXO+2gWpxGO/8IhGgqurDQKxQUUy8baolpux4f2dickYU\nUIU0FZKdciXezzwDTJ7MxITIdnyHJmuxj0J+Xq7R6DbG+1PpifcTT+yJ1auBm24CZs8GgpJ3FxNv\nG2uJKRPv70zsc0YUcLbMycSRdsVJJt7t7e1obPw6Lr20G7sl3tHDlphwImgKGk6lQUS+s2U+NlNx\nvrI4JvhkG85zRkRG4hxnzmBiQmQf4+Y5E5FRIvKoiLwgIo+IyIgc+40QkXtFZJ2I/F1EjvK6rGQm\n9lEIhkJH2jHeAzN1vrJSMd7hwnhn8vMO/j6AP6vqIQAeB7Awx35LADykqlMATAOwzqPyEREREXnO\nt2ZNEVkP4DhV3S4inwXQoqqf67PPcAAdqnpQgc/JZk0yBpuZChOUZk3Gm4iKZVyfMxF5U1VH59pO\nPDYNwC0Anke81mwtgEtU9YMcz8nkjIzADu7Fsb1DO+NNRKXwJTkTkf8GMDb9IQAK4AoATX2SszdU\nde8+f18D4EkAX1TVtSJyI4B3VLUhx+sxOQuRlpYWI2eVDkpNkNfy1Twx3uFiarzJHWGNd67kzNV5\nzlT1xAEKtF1ExqY1a76WZbctADar6trE9u8AXD7Qa0ajUVRUVAAARo4ciaqqqlTAkx0OuR2M7c7O\nTqPKk9weNmwYKiu78eyzAABUVcU7uO+22zosW7YMF110kVHlNWW7tbV1wN8z3uHaNjXe3HZnOyzx\nTv7c09ODgfjZrHk9gDdV9XoRuRzAKFX9fpb9ngBwoap2i0gDgCGqmjVBY80ZmaC9vR3NzXWorX0/\n4/G2tiGYNavViglhqXCMNxGVyripNABcD+BEEXkBwAkArgMAERknIn9M2+87AO4UkU7E+51d63lJ\nyUjp30RMwqVkwoXxJiKncRJaslY0GkVTU5PfxcjK9g7uJmppaUk1EZiG8XaeyfEm54U13r70OSMK\nq+S6h5xaIRwYbyJyEmvOyCotLS2p5sxFixahoSE+cLe+vj6U37qIiMherDmjQOibhDU2NvpWFiIi\nIjew3p2slW8oMgWLqQNAgioWi6G9vR3t7e2IpY928Igt8fb7PAWFLfH2CpMzslZVVZXfRSAKpK6u\nDkSjNWhurkNzcx2i0Rp0dXXk/8OQ4Xkit7DPGRERpXDFg8LwPJETTJznjIiIDNPR0YHKym6k5xaR\nCDB5cndqNKpfTGpCNPk8kf2YnJG12EchXBjvcOkbbzYhBhvv70xMzoiIKMXEFQ9isRgWL74A0Wgn\namvfR23t+4hGO7F48QW+1aCZeJ4oONjnjIiIMpi24oGp65eadp7IPpznjIiICsIVDwrD80Ru4VVE\n1mIfhXBhvL0ViURQU1ODmpoaXxKO9Hib3ITo93kKCt7fmVhzRkRERotEIliwYEWWJsQVTIgokNjn\njIiIrBCLxdiESIGSq88ZkzMiIiIiH3ASWgoc9lEIF8Y7XBjvcGG8MzE5IyIiIjIImzWJiIiIfMBm\nTSIiIiILMDkja7GPQrgw3uHCeIcL452JyRkRERGRQdjnjIiIiMgH7HNGREREZAEmZ2Qt9lEIF8Y7\nXBjvcGG8MzE5IyIiIjII+5wRERER+YB9zoiIiIgswOSMrMU+CuHCeIcL4x0ujHcmJmdEREREBmGf\nMyIiIiIfsM8ZERERkQWYnJG12EchXBjvcGG8w4XxzsTkjIiIiMgg7HNGRERE5AP2OSMiIiKyAJMz\nshb7KIQL4x0ujHe4MN6ZmJwRERERGYR9zoiIiIh8wD5nRERERBbwLTkTkVEi8qiIvCAij4jIiBz7\nLRSRv4vIsyJyp4h8xuuykpnYRyFcGO9wYbzDhfHO5GfN2fcB/FlVDwHwOICFfXcQkYkALgRQrapT\nAewG4BxPS0nG6uzs9LsI5CHGO1wY73BhvDP5mZzNAbAy8fNKAKdn2WcHgF0AhorIbgCGANjqTfHI\ndG+//bbfRSAPMd7hwniHC+Odyc/kbF9V3Q4AqvoqgH377qCqbwG4AcDLAF4B8Laq/tnTUhIRERF5\naDc3n1xE/hvA2PSHACiAK7Ls3m+YpYgcCOBSABMBvAPgdyJyrqre5UJxyTI9PT1+F4E8xHiHC+Md\nLox3Jt+m0hCRdQDqVXW7iHwWwGpVndJnn7MBnKiqFya25wM4SlUvzvGcnEeDiIiIrJFtKg1Xa87y\neBBAFMD1AM4D8ECWfV4AcKWI7AngIwAnAFiT6wmzHSARERGRTfysORsN4LcAJgDYBOBsVX1bRMYB\nWKaqpyX2W4B4EtcLoAPAN1X1Y18KTUREROSyQK0QQERERGQ7a1cIKGIS2xEicq+IrEtMZnuU12Wl\n8hUa78S+ERF5WkQe9LKM5JxC4i0i40Xk8cR93SUi3/GjrFQ6ETlZRNaLSLeIXJ5jn6UiskFEOkWk\nyusyknPyxVtEzhWRZxL//iIih/lRThNYm5yhgElsE5YAeCgx2GAagHUelY+cVWi8AeASAM97Uipy\nSyHx/gTAv6vq5wF8EcC3ReRzHpaRyiAiEQA3AfgnAJ8HMK9v/ETkFAAHqepkABcB+LXnBSVHFBJv\nAC8CqFPVaQB+BGCZt6U0h83JWd5JbEVkOIBjVfU2AFDVT1R1h3dFJAcVMmkxRGQ8gFkAbvWoXOSO\nvPFW1VdVtTPx807Ev3jt71kJqVzTAWxQ1U2JfsR3Ix73dHMA3A4Aqvo3ACNEZCzIRnnjrapPquo7\nic0nEeL72ebkLO8ktgAmAXhdRG5LNHPdIiKDPS0lOaWQeAPAzwEsQJZ588gqhcYbACAiFQCqAPzN\n9ZKRU/YHsDltewv6fxj33eeVLPuQHQqJd7pvAmh2tUQG83MqjbzKncQW8eM7HMC3VXWtiNyIeHNJ\ng9NlpfI5MGnxqQC2q2qniNQn/p4M5cD9nXyevQD8DsAliRo0IrKYiMwEcD6AWr/L4hejkzNVPTHX\n70Rku4iMTZvE9rUsu20BsFlV1ya2fwcga6dT8p8D8T4GwJdFZBaAwQCGicjtqvoNl4pMZXAg3kis\nufs7AP+pqtnmSiRzvQLggLTt8YnH+u4zIc8+ZIdC4g0RmQrgFgAnJ5ZwDCWbmzWTk9gCOSaxTTSL\nbBaRysRDJ4AdxW1VSLx/oKoHqOqBAM4B8DgTM2vljXfCCgDPq+oSLwpFjloD4GARmSgin0H8nu07\nwvpBAN8AABE5GvH1lbd7W0xySN54i8gBAH4PYL6qbvShjMawdp6zIiaxnYZ45/DdER8Jcn5ah0Oy\nRKHxTtv/OACXqeqXvS8tlauQeIvIMQBaAXQh3uypAH6gqg/7VW4qjoicjPiI+giA5ap6nYhcBEBV\n9ZbEPjcBOBnAe4i/fz/tW4GpLPniLSLLAJyJ+D0vAD5W1en+ldg/1iZnREREREFkc7MmERERUeAw\nOSMiIiIyCJMzIiIiIoMwOSMiIiIyCJMzIiIiIoMwOSMiIiIyCJMzIvKUiIwVkVUiskFE1ojIH0Xk\n4AH2nygiXR6X8duJ8vUm5lzr+/vBIvJ6Yumo9Mf/ICJnFfE640Tkt3n2OU5E/ivH717KVj4ishuT\nMyLy2h8QX71hsqoeCWAhMtfYzMbrCRn/gviKIpuy/VJVPwDwMIAzko+JyHDElxDLmkj1JSKDVHWb\nqp5dwO65jp8TVRIFEJMzIvJMYkHjXaq6LPmYqnap6l8Tv18sIl0i8oyI9EtaROQ8EflF2vZ/iUhd\n4ud3ReQ/ROQ5EXlURI4SkRYR+V8ROS3t738vIs0i8oKIXJ+tnKr6jKq+jPgs5bncDWBe2vYZAB5R\n1Q9F5EgR+R8RaReRv4jI5LTXf0BEHgPw5/RawcTPrSKyNvHv6LTnHpGoYVwvIr9KPyVp5+JrIvI3\nEXlaRG4WkYHKTkQGY3JGRF76AoD2bL8QkTMBTFXVwwCcCGCxiGSrUctVWzQUwJ9V9QsAdgK4GsDx\niC8Hc03aftMAnAVgKoC5IrJ/KQcC4BEA1SIyKrF9DoBViZ/XAahV1RoADQB+kvZ31QDOVNWZfY7n\nNQBfUtUjEs/1i7S/ORLAtwFMQXx9wjPTCyIinwMwF8AMVT0cQAzA10o8LiLy2W5+F4CIKKEWieRG\nVV8TkRbEk5JC+5t9pKqPJn7uAvChqsYSNVMT0/Z7TFV3AoCIPJ/43SvFFlZVPxaRBwF8VUTuA1CF\neMIGACMB3J6oMVNkvtf+d471fXcH8BsRqQLQC2By2u+eUtVNiTKvQvxc3Zf2+xMAHA5gTaLGbE8A\nXCCcyFJMzojIS38H8NUC983WLPcJMmv890z7+eO0n2MAPgLiKyqLSPp73UdpP/di4PfBfH267gZw\nZaJMD6hqb+LxaxDvV3emiEwEsDrtb97L8VyXAnhVVaeKyCAAHwxQjr7bAmClqv7w/7dvxyp1BFEc\nxr+/gZQGA0IgJGU6wUqbpMwD5AVCAqmElOmsRbCxEAufQdBakqDYCSKXFFaCYCHkJU6KWfEagl5T\nyAjfr9lld2dntxkO55y543slPQKWNSU9mKr6CTxN8uXqWpK5JG+BQ1qZcSrJLPAOOLp6bDieA/Np\nXgELY6+/rcfqf/uvcsfYfVqGa4nrkibANNfZuM8TzvUMuBzOPwJPxu4tDj1pU7Ty5eFfY3/QMniz\nAElmkryecF5JnTE4k/TQPgDvh0b9X8AKcFlVO7Ry5Aj4Dnyrqt/DmAIYNg6c0zJw69zsX7sty3Wv\n3Y5Jvia5AF4CoyRb/xxcVcA28LyqDsZurQGrSY6ZfJ3dBD4lOQHecDPDdgRs0P77rKp2x7+/qk6B\nZWAvyQjYA15MOK+kzqStLZIkSeqBmTNJkqSOGJxJkiR1xOBMkiSpIwZnkiRJHTE4kyRJ6ojBmSRJ\nUkcMziRJkjpicCZJktSRP3WSlzkLi2oGAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116a0c550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotData()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best C, sigma pair is (0.300000, 0.100000) with a score of 0.965000.\n"
     ]
    }
   ],
   "source": [
    "# Your task is to use the cross validation set Xval, yval to \n",
    "# determine the best C and σ parameter to use.\n",
    "\n",
    "# The score() function for a trained SVM takes in\n",
    "# X and y to test the score on, and the (float)\n",
    "# value returned is \"Mean accuracy of self.predict(X) wrt. y\"\n",
    "\n",
    "Cvalues = (0.01, 0.03, 0.1, 0.3, 1., 3., 10., 30.)\n",
    "sigmavalues = Cvalues\n",
    "best_pair, best_score = (0, 0), 0\n",
    "\n",
    "for Cvalue in Cvalues:\n",
    "    for sigmavalue in sigmavalues:\n",
    "        gamma = np.power(sigmavalue,-2.)\n",
    "        gaus_svm = svm.SVC(C=Cvalue, kernel='rbf', gamma=gamma)\n",
    "        gaus_svm.fit( X, y.flatten() )\n",
    "        this_score = gaus_svm.score(Xval,yval)\n",
    "        #print this_score\n",
    "        if this_score > best_score:\n",
    "            best_score = this_score\n",
    "            best_pair = (Cvalue, sigmavalue)\n",
    "            \n",
    "print \"Best C, sigma pair is (%f, %f) with a score of %f.\"%(best_pair[0],best_pair[1],best_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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R5M3D3NhkZ+c8XGFOx52KGCvidNxOlcMtcTshVbG77Ri7rTypYnfc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\nEkSdNxEREZEEUedNREREJEH+P5op/LpUaFloAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113dd25d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gaus_svm = svm.SVC(C=best_pair[0], kernel='rbf', gamma = np.power(best_pair[1],-2.))\n",
    "gaus_svm.fit( X, y.flatten() )\n",
    "plotData()\n",
    "plotBoundary(gaus_svm,-.5,.3,-.8,.6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2 Spam Classification"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
